{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "s1 = Series(np.random.randn(1000)).cumsum()\n",
    "s2 = Series(np.random.randn(1000)).cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x110230eb8>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1.plot(kind='line',grid=True, label='S1', title='This is Series')\n",
    "s2.plot(label='S2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OGd6dBVuzOVBgX/vkkT4iXYBObxgKymuJa/CG//NdU/jshnH2B2Yb5LPXvG1d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\niIjkUGIQEZEc/wcRBkwePFT2ewAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fccf4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(2,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x10fd43eb8>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x10fb2cda0>], dtype=object)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1109d1940>]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax[0].plot(s1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10fb76668>]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax[1].plot(s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PV56/eJgpPQNo+fytYYysnWQI8rrnq91MeHENYKn2sabu6QgcSjoWlzuXSgcw\npXyt1mvh3z4erhwyFKWOCfW159DaDXdXHb4eruSVVrI/pYC/vKkFu9TNgmhc4Zun+03PL8e/u+12\nPjtO5zKsZ4DV+r/2wKhPD/O1vTon2hCclFdaibe7KxP7hLD1VE69ouRGYrv58sS8QcQnOkYq64gA\nL76+bQJ7kvNxd9VZLRFqTF8+olcgt0yJ4cM/T5NRWE5eSSUHzHz4zxZW2OVH0GFW+J9tTaSsqsbu\nvr4dza2GAK1F8wYBWrqEHYb6r4PtHOjSnoT7e5CcW8Z9S3bXO3frlBjcXXUmd9WNx7NN5zKL2qb3\nl1Ka9LJP/nSAK9/dyqsrj7bpnrbEqFrw97L9wmeIoTLWdRN6A1qJTiP9utVfXCy9ezLTBnTj4fM6\nb36mljKxbwh3TuvLhcMjWDCuF1ePjzKdu29mLK5mrtTmpRkPpReydFetV89Lvx/umAHXwWGWw0/9\nfBBoXXWcrswT8wZx78xYk5rDmKAq3N+jSxvKmqJnkLcpfXRdJseGsuFYlkm9cd/XtT8K/1t/knNi\nW5+G+56vd5OQmMeKB6by+TbNOFo34MaeGKs2tcdO199Ti/I2MiqqtlDO8J4BRAR4sul4NufEhvLa\nlSMdercd7u/JS5cOp7C8ypRZs27WTT8zN9iDaQUknMljWM8A9qcWsOl4NuVVNVaTJ7YnDrPCn9xP\n05nNHNQhhbU6DUIIC+OsMRWDsYato3LTpGiL4/hFswj19eDRuQOYPqAb3QM8ySgor+ceWN0GY1ly\nbinL96WTUVjOlpO1u4aSTpS506i+8uuAIjZzh3bniQu0nWU3f0/eumY0I3sFsmjeYIcJ8msKf083\nbpio7XjquoObO5C8+NsRknJKLWpF55Z0vB7fYQS+Xg9jo4OajE51dIylELv7t49LXmfBvERkz0Av\nQn09iF80i7umaYmvIgI8ySgstwh+mT04nMI2pGSYaVYM484vd5leG3cSnYFnfjkE0GHOC7dMieG5\n+UN4YFYs/p5u/HT3ZLsW0LEH8wwBauf2D7VonzWom6manZGoYC9evkwzftsjxbfDSEdn88FviBhD\niuPOXvHLlqRZEbh+nm6cLazgky2JgGZMC/Rya1MOHmtC9OrxUeSXVpncIe3J9wm13jIeHZQIT6cT\nXDcxusNVE52JcTHBJC6eR79ulj90Qoh6JUmHRQYSbMjma4/gNMcS+HasxdpZuHlyDIsvHcbNk2Oa\n7uwg9LBEA3m6AAAgAElEQVRSAs/H4DXz4Z+ncdEJvr5tAgFetfVaG+NMTilnckrZfCLbwl86xNed\nOYPDuWBYd1Pb2GhNj23tR6ejefg7zSX1odn9HSaq2tEY0zvIlJrCIVf4Qoi5QoijQogTQoiF7fUc\ntcLX8HRz4apxUZ3GTbAjePe6MfXa7pjW1+QTfeHwCIJ83An0dqOsqqbJcn1T/7WOqf9axzUfbOeb\n+GRySyrR6yWnskoI8XXnvwtGA3DV2F6meqvpnSjq11xPrOg8vHW19rkxfjevfHcrb6070dglNqdd\nJaQQwgV4C5gNpAA7hRDLpJSHbP0szQffeYScQlvJJueWWlVfebu7Etc7iO2nc021TQOMEbplVXTz\na95nZWdiLo/9WJsUrE+oLy46weFn52qun4a8Kp1hhW/E2TzVugrzDNXEzJPP/WvFUe62UkS9vWjv\nJfE44ISU8hSAEGIJMB+wqcCvrtFTVlWDr4dS6TgT5pGP1hjfJ4Ttp3M5x2BMM3ozFZZV0c2v1qh9\nIrOY/an5JGaXWviWA+xLsSx4MSVWu5dxlRYeoOlj7bXCl1Ky6tBZ4gyr+r5hPg7vodXVuG5Cb05l\n16ZK9q6z+84vraxXfrS9aG+B3xNINjtOAcabdxBC3A7cDhAVFUVrKKnQtui+TpZWQdE4983ox7UT\nokzC3Zg91FyPn19ayazXNli9HmqrNRnxcbf8jHm4uhDq60Fqvn3y8286ns3tnyeYji+uYyRU2J/n\nLh5qcVw339fD3+3jnNhQbqjjatwe2N1oK6V8T0oZJ6WMCwtrXUBMsaG+qZ/S4SvMcHXRWazkjTEK\n5mX/Pt2SZPXar24bj7sVF19vK2rDIT38+TY+hTUNBIK1J3Urm/V24GA7RyHYx3I1v/rwWZ5edrBD\nnt3eAj8V6GV2HGlosynFhnBytcJXNEZsuC9uLoK9ZmqaX/fV5t8xr7k6qW8oY2M0D5yZZj7/dVf4\nABP6aEF/t3wab/MxN0Vd28GEPspg29lxsWPlr/YW+DuBWCFEjBDCHbgKWGbrh5RX1eDj7qK8dBSN\n4unmwpAeASSYJfNKyik1+awbdd9Go6dxdxBktiKrGz4PWn4VI9UdXIUrq6iCmFAfZg7shotOWOxo\nFJ2Xbn4e9Kxja6mbO789aFcJKaWsFkLcA6wAXICPpJQ237uM6BXIwWfn2vq2CgdkaE9/ftmr5Siv\nrNZTWaPnxknR/HEgg1unxPDkvMEE+mi6fqOR13wLbs2/fajZziCzqKJFRlMpJSl5ZQ0W1m6KzMIK\nwnw9eP/6OGo6QGAobMOf/9CqkfVf9LupTUvv3r6OJ+2uw5dS/ial7C+l7CulfKG9n6dQNEaQtztF\n5VVU1+hN6W17BXuz7fGZjO8TQlSIt6n2q3HrHeTtzooHptYLkzfi6qLjlcuHAy3Pc/5dfArnvLKO\n3WdalkL4TE4pafll7EnOZ2jPgGYVvVd0HtxddfUKpheZlZFsL5QOROFU+Hm6opfQ74nalVVD8RvG\nIukerjoGdPdrNEeMcXte3MIv7UFDjvSEpDyL7JONUaOXTP3XOtPxtAGtz/6p6Dx0hMBXSwKFU+Fv\nZcvsbcUQC7UC360ZeWmM9iNjeuLmYiyCkWPInJhfWml6rjXWHjlLQpLlbmCIA9c9cHTM8+k/vnR/\nIz1tgxL4CqfCmo60oURjRrdM72YkBjN6iLVU4Bvro1ZV6ymrrGHks6t4/lfrcYkJSbnc/Ek8V767\n1aK9K5cPdHZevGQYP9yp1fvtiHTJSqWjcCrq+kD3DPRiUr9Qq30fmj0ATzcX/jKiR5P3NcaAtHRb\nftBQjvKjzadNOt3fD2Twz/lD6/U9nF5Ur82Yj17RdTHm0e8Il1ol8BVORZ8wy8Ckd68b06A7b4C3\nG481U6C2ZoV/MK3AVLVLL+Ht9ScBiGjAy6duaufNC2fUc+1TdD2G9gzgnWvHMH1g+9tilMBXOBXd\n/DzwcnNhQHc/okO8GRRhG/23l5sLOtE8o21heRW/70+3qFRmTkZBGRXVNby/8RTTB3ZjSA8tv09+\nHQ+gjipyomh/5g7t3nQnG6A+MQqnQgjB4edsH7MhhMDXw7VZK/ynfjrAT3vSWDBOM9jdPrUPOiH4\n6M/TVNboOVtYwYBFfwDw6spjvHzZMHoGepvcSI34NmBsVigaQn1iFAob4efp1iwd/unsEgCOndV0\n8vfPjMXHw5V/zB3AdwkpPPr9Pov+//ih1ntjUIQ/h9M1vb/OjiH6iq6J8tJRKGxEtV7PD7tSmuxn\nNM4mJOXh5iJM6XKFEIT4NJ4mV+XKUbQFJfAVChtxtlDLwpmc2/xUya46nUW6hkDvhkPrzxsS3qHF\nMhSOhxL4CoWNMNa6PWRQuRg5fraI+W/+SYEhD39hWbXJjbOsTiHrAC/LFf5TFw4mKtibz24ex7vX\nxRHq68Fv953Dpkent9c0FA6MEvgKhY14/uJhAKayh0b+s/oYe1MKWHtUc8EsKq9ian/NBa+uW6X5\nCt/LzYWbp8Sw8dHppv4Ag3v4tzrZmsK5UUZbhcJGBHq54aIT5JRUWLQbA2uKDZXZCsurCff35Oe7\nJ9cLBAvxccfPw5Wiimo+vmlsxwxc4TQoga9Q2AidTjO6ZhdZD5HPLqqgqLyK4opqQnzdGdErsF4f\nIQQJT87GRSfsWihD4Zgoga9Q2JBgH3dTIjQjWUXair+ovJojhpKEA8IbzrxZN22uQmEr2vTJEkJc\nIYQ4KITQCyHi6px7TAhxQghxVAhxXtuGqVB0DQK83Cgqr02BIKUko7Ac0CJs31hzHE83HXHRzUuF\nrFDYkrau8A8AlwLvmjcKIQajlTMcAvQAVgsh+kspa+rfQqFwHPw83UjNL0OvlyTlljL91fWmc2cL\ny9l6MocF46II9G7c316haA/aJPCllIfBatm3+cASKWUFcFoIcQIYB2yt21GhcCT8vVw5nF7F1R9s\nY9upXItzm45nA1qZRYXCHrSXDr8nsM3sOMXQplA4NJmFFaTml5Gab+maKQQYS85GBftYuVKhaH+a\n1OELIVYLIQ5Y+ZtviwEIIW4XQsQLIeKzsrKavkCh6MSc2996ituvb5tget07RPnQK+xDkwJfSjlL\nSjnUyt/PjVyWCvQyO440tFm7/3tSyjgpZVxYmKrNqeja3Da1D5FB9XPU9wn14a5pfQHo7u/Z0cNS\nKID2i7RdBlwlhPAQQsQAscCOdnqWQtGpsJYAzdfTlUfOG8Dply5QWS4VdqOtbpmXCCFSgInAciHE\nCgAp5UHgW+AQ8Adwt/LQUTgLxuhZN5dawe7l5oIQwpqDg0LRYbTVS2cpsLSBcy8AL7Tl/gpFV8TH\nkBjtznP7EuLrwXcJyUrQKzoFKtJWobAxfcJ8ARgY4c8FwyK4YVK0fQekUBhQAl+hsDH3TO9Hv26+\nzB3SMXVKFYrmogS+QmFj3F11XDSih72HoVDUQ2VpUigUCidBCXyFQqFwEoQ0xnt3AoQQWUBSG24R\nCmTbaDhdAWebL6g5Owtqzi2jt5SyycjVTiXw24oQIl5KGdd0T8fA2eYLas7Ogppz+6BUOgqFQuEk\nKIGvUCgUToKjCfz37D2ADsbZ5gtqzs6CmnM74FA6fIVCoVA0jKOt8BUKhULRAErgKxQKhZPgEAJf\nCDFXCHFUCHFCCLHQ3uOxFUKIXkKIdUKIQ0KIg0KI+w3twUKIVUKI44Z/g8yueczwPhwVQpxnv9G3\nHiGEixBitxDiV8OxQ88XQAgRKIT4XghxRAhxWAgx0ZHnLYR40PCZPiCE+FoI4emI8xVCfCSEyBRC\nHDBra/E8hRBjhBD7DefeEK1Nvyql7NJ/gAtwEugDuAN7gcH2HpeN5hYBjDa89gOOAYOBV4CFhvaF\nwMuG14MN8/cAYgzvi4u959GKeT8EfAX8ajh26Pka5vIpcKvhtTsQ6KjzRqtvfRrwMhx/C9zoiPMF\npgKjgQNmbS2eJ1oBqQmAAH4Hzm/NeBxhhT8OOCGlPCWlrASWADapt2tvpJTpUspdhtdFwGG0L8t8\nNAGB4d+LDa/nA0uklBVSytPACbT3p8sghIgE5gEfmDU77HwBhBABaILhQwApZaWUMh/Hnrcr4CWE\ncAW8gTQccL5Syo1Abp3mFs1TCBEB+Espt0lN+n9mdk2LcASB3xNINjtOMbQ5FEKIaGAUsB0Il1Km\nG05lAOGG147wXrwOPArozdoceb6greaygI8NqqwPhBA+OOi8pZSpwKvAGSAdKJBSrsRB52uFls6z\np+F13fYW4wgC3+ERQvgCPwAPSCkLzc8ZfvEdwrdWCHEhkCmlTGiojyPN1wxXtG3//6SUo4AStK2+\nCUeat0FnPR/th64H4COEuNa8jyPNtzE6ep6OIPBTgV5mx5GGNodACOGGJuy/lFL+aGg+a9jmYfg3\n09De1d+LycBFQohENNXcDCHEFzjufI2kAClSyu2G4+/RfgAcdd6zgNNSyiwpZRXwIzAJx51vXVo6\nz1TD67rtLcYRBP5OIFYIESOEcAeuApbZeUw2wWCJ/xA4LKV8zezUMuAGw+sbgJ/N2q8SQngIIWKA\nWDRjT5dASvmYlDJSShmN9v+4Vkp5LQ46XyNSygwgWQgxwNA0EziE4877DDBBCOFt+IzPRLNPOep8\n69KieRrUP4VCiAmG9+t6s2tahr2t2DayhF+A5sFyEnjC3uOx4bymoG339gF7DH8XACHAGuA4sBoI\nNrvmCcP7cJRWWvI7wx8wjVovHWeY70gg3vB//RMQ5MjzBv4JHAEOAJ+jeaY43HyBr9HsFFVoO7lb\nWjNPIM7wXp0E3sSQJaGlfyq1gkKhUDgJjqDSUSgUCkUzUAJfoVAonAQl8BUKhcJJcLX3AMwJDQ2V\n0dHR9h6GQqFQdCkSEhKyZTNq2nYqgR8dHU18fLy9h6FQKBRdCiFEUnP6KZWOQqFQOAlK4DsZUkoO\nphVQXaNvurNCoXAoOpVKR9F+ZBdXEOrrwZjnV5NbUkmwjzs/3z2ZXsHe9h6aQqHoIJTAd3AOpBbw\n3K+H2H46l25+HuSWVAKQW1LJD7tSeGBWfzuPUKFQdBRKpeOgSClJySvlyne3sv20lo47s6gCgHum\n9wPg9dXHScsvs9sYm+KBJbv5escZew9DoXAYlMB3UL7ekcyUl9dRWlkDwJjeWhU1Xw9XHj5vAP26\n+QLw7C+H7DZGa3wbn0z0wuVEL1zOT3vSeOzH/RSUVdl7WAqFQ6BUOg6IlJLHl+43Hf941yRGRAay\nfH86IyMDAVjxwFQe+3Efv+xNJ6+kkj3J+cRFB+Hn6dbh4/3jQAZHMgq5d0Ysj36/r975vcn5TO3f\npIuxQqFoAiXwHZD1R7NMr/c9Mwd/gxC/aEQPU7uLTnBlXC++jU9h1HOrAFgwrhcvXTq8Q8daVaPn\nji+0eif/W38SAJ0AvQQvNxfKqmrYfCJbCXyFwgYolU4nZevJHBb+sA+9XvL7fm0V3hxOZhVz0yc7\nAVh61ySTsLdG/+5+FscZBeVIKTmVVUxVB7htZhVVEPvE76bjimo9QsCWhTM59vz57H16DoHebnyy\nJdFkbDaSXtB5bQ8KRWdFCfxOyoL3t7FkZzJ9Hv+NO7/cxZSX17L7TB5NpbP+cZdW+vLhOf0ZFRXU\naF9/TzfcXWo/AuuOZhHz2G/M+PcGHvxmT9sn0QTrj2aaXl8xJpLZg8PZsnAG3QM8cXfV4e6q4/Ob\nx1NRrWfeG5v4dV8aAEcyCpn40lrTjkChUDQPpdLpROxMzOWKd7by99n1XSVLKmu45O0t9Ovmy+/3\nn4Obi/Xf6tS8MsL9PbhnRmyznrn8vin4erqSVVTBRW9urm3fn84/cktJyy9jfJ+Q1k2oDlJKtII9\nGieyigHY/eRsgnzcrV4zLDKA2G6+HM8s5p6vdjM6KogTmdp1X25P4s5pfW0yNoXCGWjzCl8I0UsI\nsU4IcUgIcVAIcb+h/RkhRKoQYo/h74K2D9exueKdrQD8e9UxzOSiBScyi/l0S6LVc+9sOMlPe9Io\nM3jmNIfYcD8iArwYHhnI5oUzGBUVyBVjIpESznllHX99bxsfbDrFHZ8nUFltqeYpLK/iu/hkq7uO\nIsM5vV4799TPB5j/1mZThG+NXvLz7jQGRfg3KOyNvHXNaNPri9/azC97tZV+Sl5Zs1VdCoXCNiv8\nauDvUspdQgg/IEEIscpw7j9Syldt8AyHp6SiGhedoMYgIKWEHgGe9Aj04u1rRrPxeDbVNXoW/rif\nL7Ylces5fSyur67Rs/j3IwCtNnD2DPRi6V2TOZ1dwncJKab255cfBuDDP09z57S+ZBaW88wvB/lt\nfwYA8Yl5TOgbzJzB3amo1hPk7cZb607yzoaT+Hm6MndoBJ9t1XI7fbY1iSmxocz5z0YA5g2PaHJc\n/cP9OP7C+Yx+dhWZRRXsMMQVADzwzR5CfT14+bJhuDaw61EoFBptFvhSK7CbbnhdJIQ4DPRs632d\njQXvb6NGL1kwLsoUbPT17RPoHeIDwOVjtKL1mUUVvLbqGCl5pUQG1aZF+O2AJnxfunQYFzZDiDZG\nTKiP1XajKuWDP0+bhD3AN/HJfBOfzLQBaRYeQgB3fLGL/7tqpOn42V9r/f57BnqxaN6gZo3JzUXH\njZOj+e/aE+SVVrHw/IEs/v0IG45pzzt/aHdmDQ5v3gQVCifFpksiIUQ0MArYbmi6VwixTwjxkRCi\ncQuik7LhWBY3fbyDfSkFzBsewYuXDGXTo9NJXDzPJOzNGRsdDMCUl9exNznf1P7L3jR6BHhy+ZhI\nm/jS3zolhkfOG0DPQC8AJvcLYdupHP675jgrDmYwKiqQxMXzGBThb7qmrrA3cv+SPbjqBJeMslwH\nrHt4moVOvykuGFb7Q3bpqJ4Em6mCXlt1zLQ7UigU1rGZwBdC+AI/AA9IKQuB/wF9gJFoO4B/N3Dd\n7UKIeCFEfFaWdYHhqGQVVXDDRztYZxCUiy8dhhCi0YRm42KCTVGz89/azOYT2QCcyipmaM+ABo25\nLWXRhYO5e3o/frvvHHY8MZMxvYNJzS/j36uOkZRTSqCX9qPy1a3j2fv0HB6dO8B07SPnDcDf05Xl\n900xtc0ZEs5//jqS964bg7e7C3dN64u7a8vGOijCn71Pz2HvU3Po5u/JL/dOYfVD5wJwKL2QZXtT\nbTBzhcJxsYl0EEK4oQn7L6WUPwJIKc9KKWuklHrgfWCctWullO9JKeOklHFhYY4bXLN8XzrRC5eT\nWVQOaB4rRhfKEB933rtuTLNW5i46wQ93TmJEZAAA13ywneiFyzmZVdKkG2ZrCPB2o5ufJzMHdrNo\nXzAuCoAgH3cCvNy4fmK06dzd0/ux75nzGNIjgPtm9GPO4HBevkwL6JozpDuHnp3Lo3MHtm48Xm4E\neGvvU89AL/p18+WOczVPnQe/2Ut5Va3BOiEpr0UGbIXC0WmzDl9oe/IPgcNSytfM2iMM+n2AS4AD\nbX1WV+a9jZrP+DPLDnLpqEh+2pPKr/vS8XZ3IeHJ2S2+X98wX/amFFi0XTSyRwO9287gHrWqm/9d\nM5o5Q7pbnPf1cGXJ7RPqBWw9NGcA7c3C8wfyzgbt/f3jQAZ7kvMJ9XXn1ZXHuHhkD16/alS7j0Gh\n6ArYwktnMnAdsF8IYYzWeRxYIIQYCUggEfibDZ7VJanRS46d1Qyev+3PsDB4dvf3bNU9/3H+QEoq\nqxkXE0J1jZ6yqhqTvr09cHPRsenR6QT5uOPrYf1jM8FG/vqt4evbJrDg/W08UCdgbLuZR49C4ezY\nwkvnT8Ca5e23tt7bUUjLL6Osyrpq4cMbx7bqnuH+nrx7XVxbhtViOnOxlIl9Q3jxkmEWSeNAU4E1\nRmF5FZ9vTeL2qX1sZv9QKDorKtK2A1i+X9NsvXLZcDKLynl15TFAy2LZkAukouUsGNeLAd19TQFZ\na45kcji9kJS8Us7klHIwrZBbz4mx8Ax6beUxPtmSSO8Qby4c3n4qMYWiM6AEfjtTXlXDayuPMbJX\nIJePiUSnE+SWVLHuaCaDzVwaFW1HCMGY3sGM6a0dS2DT8WymvLzO1Gdq/zD6hvmYgrSMRvTkXJWM\nTeH4qD1sO3P/kt1U1ug5t38YOoN64am/DGbNQ+fi6eZi59E5NlfE9arXdt7rG5n52gZKKqpZ/PsR\nkz0lKaeko4enUHQ4SuADh9MLySmuQErJ7jN5vLPhJHd8nkBReeOVlqSUlFfVNJjBsrpGb/Kxv7hO\n0JGuCd2you34eriSsGgW0weEEWIWpJWUU8otn+40efYALNmZTElFNQAbj2U1+X+vUHRFnF6l8/Oe\nVO5fsofhkQGMiw7mgz9Pm84Ferux+LL6BUEOpRXy/qZTLN2tBfo8PKe/1eyUu5PzqazW8+oVI5Su\n3k6E+Hrw8U1aCMjyfel8l6AJ9m2nar13XrhkKE8sPcDn25K4fEwk13+0g7HRQXx3xyR7DVuhaBec\nfoX/5TYtb82+lAILYe/r4co38cnsS6lNX3DsbBF5JZX844d9JmEPmIywRnadySMxu4QXfzuMp5uO\nWYMsg5YU9mHe8Ag+uWkcdxmKuAPEL5rFNeN7M7V/GO9tPMX+VC22YWdinr2GqVC0G04t8Esrq9md\nnMfoqECL9vOGhPPfBaOQEi56czPL9qZx/GwRc/6zkYve+pPU/PoGvuiFy9l6Mge9XnLp21uY9up6\ndp/J57HzBxHo3Xj6X0XHMiGmNl4g1NcDgPtm9CO3pJI7Pk8wncss1Ay6W05ks+uM9gPw2/50Hliy\nmxOZRR04YoXCNjilSqdGL/nru1uJT9K+xHdN68fjS/dTVaNn3cPT8Pd0o0ZK/jKiB7/sTeO+r3eb\nrjV6cxjVOP9acYS31mm64Hu+2mVKOWBk2gDHTRfRVfFyd+HjG8da2FHG9A4ixMedHLP8+nNe30iw\njzunsjSD7pq/n8tdX+4CYMvJHLYsnKFSMiu6FE75aT1bWG4S9qC56u14Yha7npxNoLc7Op3AzUXH\nsxcNafAextTEN02OMbXllFTy5roTDI7wZ1LfEOJ6B1nNeKmwP9MHduNcs7oBQgjOH1abLiKudxD5\npVUmYQ8w898bAC19dGZRBXvMspU2l4yCcvJLVdEWhX1wSoFvrpJ5+i+DTVkb66bqDfSuTWa27J7J\nHHv+fNNx/3CtAHiorwcPzurPKDO10HMXD+Gr2ybw/Z3K6NeVeHTuQO6d0Y/Dz87lsQsGMn9kD9Y9\nPI0JfYIt+n1ykxYdnZhT2uj96qZr3n4qhwkvrWHks6vYeKxlmWFziit4ffUxDqQWNN1ZoWgAp1Tp\npOTVflGNqYatIYRg/cPT6B7gafKZ3/nELJbtTWNQhJ+p3/2zYrl3Rj82ncgmo6CM0e2QtVLR/vh7\nuvF3Q7I3LYBLE/RJZoL9x7smEW7If/TKH0fwcnPhgmHdLRYLBaVV/Lg7hX/+coh7Z/TjwVn90ekE\nvx+ozaG06tBZ4qKDeGDJHlYeOst9M2N5cFYsegmLfz/MFXG9iAr2xtPNhcyicsa9sAaADzedZv8/\nz2v390LhmDidwK/RS5bsSAbgmb8MZljPgEb7R9dxpwzz8+CWKTH1+ul0wkJFoHAcnrpwMHd+uYvt\nj880CXvQqo/d/dUunrxwsOkzseJgBn8zM/z+d+0J/jyRzXPzh/KVoZIZwOfbkth0PMu0S3hjzXHC\n/DyQUvL+ptO8v0nzGPv+jomsPpxpus5od/h0SyJDewY0umBRKOoiGgoasgdxcXEyPj6+XZ/x2qpj\nvLHmOACJi+e167MUjsuX25N4YqmW8dvf05Wdi2bh4erCxW9tNun2g33cya1TZP2zm8dx/Uc7Gryv\nt7sLpVZy+A8I92Ni3xC+2nGGr24dz+WGgvebHp1OXmklB1ILuXp8FEk5JUQFe7eokpii6yOESJBS\nNplN0aFX+Hq95NOtiVw4vAd3fJFAdY3elEP+/es7NtOkwrFYMDaKUb2CSMop4c4vd3EgtZCVB7Vc\n/OfEhnLP9H6MjQ4mKbeUJ5buZ8vJHPqE+TAuJpivbhvP1e9rVUAfOW8A10/szbBnVgJQWllDXO8g\nckoqOZ1dazC+fEwk0weG8V18sknYA5zzSm2eIB8PF+5foqWHPv3SBUroK+rh0Cv8HadzufLdrfXa\n753Rz6SrVSjagrl+3ciWhTPoUac2QWp+GSE+7iZbkHEn8OoVI7h8TCT5pZWMfHYVAH/+YzqRQd5s\nPpHNp1sSSS8o58vbxuPv6cZrK4/yxtoTTY7rjQWjqKrW89Hm0/znryNNTgYKx6S5K3yHEviV1XoW\n/bSfrKIKnpg3mC+3J/Hx5kSLPuNjgvn05nEqcZnCZkx4cQ0ZhiCtzQtnNKsQTXJuKT/tTuX6SdEE\nGOoDF5ZXkVdS2agrb0lFNZtPZDMowp91RzOJDPLi0y1JbGjE6+e8IeEdXjtB0bE4pcD/ISGFv3+3\nt157iI87j18wiLjoIHoGeqlgGYVN2Xwim2s+2M5Llw6rF3jXEej1kikvryWtoJxZg8KpqK5h0/Fs\niz7HXzhfFXhxYDqNDl8IMRf4P8AF+EBKubi9nvXTnlS6+3sytKc/qw9n0jPQiw9vjGNgd5V3XtF+\nTO4XytHn5+Lhap9do04nWPfINKprJD4eruj1ksMZhcx7409Tn4NphYzsFdjIXRTOQLsKfCGEC/AW\nMBtIAXYKIZZJKQ/Z+lmnsorZdDybR84bwC1TYsgvraJ7QOvqxSoULcVewt78+cZSwzqdYEiPAPY+\nPYfSymomvrSW+MRcJfAV7b7CHweckFKeAhBCLAHmAzYX+DsMxarnDYvA082F7gFKR69wbgK83Ajw\nciMyyItXVhwlPjGP/akFvHDJUKYNUBlcnZH2Vur1BJLNjlMMbTbn9wMZ+Hq4EtWJC20rFPZgdFQQ\nldV6/jiYQWp+GTd+vJODaSpFgzNidyuOEOJ2IUS8ECI+K6tl+UWMnMoqZsOxLG6cFK0qSSkUdYjt\n5g/8lh4AABB+SURBVFuvbVeSyvfvjLS3wE8FzAuLRhraTEgp35NSxkkp48LCWpeawM1Fx9Xjo7hu\nYu/Wj1ShcFCmxIYS6uvOV7eN5/RLFxDk7caB1EJ7D0thB9pbh78TiBVCxKAJ+quAq239kF7B3rx4\nyTBb31ahcAhGRQURv2i26XhozwBTZS+Fc9GuK3wpZTVwD7ACOAx8K6U82J7PVCgUjTO0ZwDHzhZR\nXlU/Z4/CsWl3Hb6U8jcpZX8pZV8p5Qvt/TyFQtE4k/uGUq2XrDiY0XRnhUNhd6OtQqHoWCb1DcHP\n05XtBldmhfOgBL5C4WTodILhkQHsT1F6fGdDCXyFwgkZ1jOQIxmFVFQrPb4zoQS+QuGEjIgMoKpG\nsvFYdtOdFQ6DEvgKhRMyvk8Ifh6uvL2+6dz6CsdBCXyFwgkJ9nHnb+f2YfeZfPLqlGG0FbkllWw+\noXYQnQkl8BUKJ2VM72AARj23ii0nbS+YH/luL9d8sJ3U/DKb31vROpTAVyiclBG9Akyv7/5yV5sN\nuFJKftyVQnFFNYApmjc+Ubl/dhaUwFconBRvd1c+u3kcz/xlMHmlVTz/6+E23e+jzYk89O1enli6\nn4SkPDKLKgDYfSafu7/aRUIzE7al5peh13eeSnyOhEOVOFQoFC1HSsnwZ1ZSVFHN+oenER3acE3d\nhigsr2L4Mysb7RPi407Ck7Mb7XP8bBGz/7MRH3cXtj8xC1+Pdi/K5xA0t8ShWuErFE6OEIIigxrm\nky2JrbpHap6mp794ZA+L9jA/D9PrnJJK3lx7HIDf96dTWF5V7z7rj2op0ksqa/hmZ3K984q2oQS+\nQqHgg+u1xWFNK1UpGQXlAFw/KZrTL13AwO5+AGx7bCY7Hp9JhKHc6KsrjzHj1fXc+eUu7v5yV737\nHM8sItTXnYHd/VSun3ZACXyFQsGsweGMigrk6NkiTmYVU15VwzPLDppKhxo5lFbIK38cwVwVnFlU\nzpaT2egERIf4IITg2zsmsvvJ2bjoBN38Pdn62ExOvHA+EQGenMouAWDT8Wyu+WAbldV6knJKiF64\nnG/jUxjSI4AZA7uRkJRndRegaD1KQaZQKACtMta38SnM/PcGPFx1VFTr+WRLIq//dSQhvu5M6BPC\nBW9sAuDq8VGUVNSwP7WAh7/bC8C5/cMI9nEHwN/Trd79XV103HFuX5buTmVPcj4Am0/k8Maa4xYG\n3avG9qKbvwdvrz/JigMZXBHXq969FK1DCXyFQgFA/3A/0+uKar3p9QPf7KnX99Mtiby/6bRF263n\nxDT5jBsmRXPDpGiW7DjDwh/3A5CUW8qxs0UArHpwKrHhfkgpCfPz4JHv93H5mEiEUKVLbYFS6SgU\nCgDG9A6yOP7hzkkN9jUX9j0DvYhfNItzYptfovSqcVEkLp5HXO8gftmbRk5JJY+dP5BYw4+OEMJk\nB9idnE9xRTVVNXo2HMsieuFyohcu55e9aS2ZngIl8BUKhYFRUUEcfnYuj50/kLjeQQyPDGBwhD8A\nE/oEm/rdNzPW4rrJ/UII9fWgNbi61K7c+4RZFls3li1dtPQAQ59ewcSX1nLDRztM5+/9ejfHzxax\n8VhWq57tjLTJD18I8S/gL0AlcBK4SUqZL4SIRitpeNTQdZuU8o6m7qf88BWKzkVmUTl5JVX0DfMh\nPimPssoaYkJ9mPbqegC+uGU8cdFBeLq5tOr+p7KKmfHvDQCsfuhc+nWrFfpSSu75ejfL96VbXPP6\nX0fyzoaTHMkoMrXteWo2gd7urRqDI9BcP/y2Cvw5wFopZbUQ4mUAKeU/DAL/Vynl0JbcTwl8haJr\nkF5QRk5xJUN7BjTduQkOpxfy5fYk/nnRUFx0lrr6Gr0kPjGXv763DdCSvu16cjaZReWMe2GNRd/Y\nbr48MKs/84ZHtHlMXY0OEfh1HngJcLmU8hol8BUKhS3JKa4gOa+MmBAfArw1D6Dohcut9j3xwvm4\nujiXtrq5At+WXjo3A9+YHccIIfYABcAiKeUmGz5LoVA4ESG+HoTUsRP8+4oRlFXV4OGqo3uAJ9d9\nqOn3L3pzM7/df449htnpaVLgCyFWA92tnHpCSvmzoc8TQDXwpeFcOhAlpcwRQowBfhJCDJFSFlq5\n/+3A7QBRUVGtm4VCoXA6LhsTaXG8ZeEMJi1ey6H0QsqralptV3Bkmtz3SClnSSmHWvkzCvsbgQuB\na6RBPySlrJBS5hheJ6AZdPs3cP/3pJRxUsq4sLDmu3UpFAqFOT0CvXj5Ms2zZ+vJHDuPpnPSJkWX\nEGIu8ChwkZSy1Kw9TAjhYnjdB4gFTrXlWQqFQtEUxqIuj3y/j/IqVaC9Lm21bLwJ+AGrhBB7hBDv\nGNqnAvsMOvzvgTuklKoKgkKhaFf6dfPl2glRZBdXMPyZlVTX6Ju+yIlQ+fAVCoVDUVJRzZCnVwBa\nUFh3fy8emBVLr2BvO4+s/VD58BUKhVPi4+HKqRcvALTkbD/sSuHZXw/ZeVSdA5U8TaFQOBw6neDh\nOf1ZcyST3sHerD2SiZTS6ZOwqRW+QqFwSO6ZEcvSuyYzuncQheXVnC2ssPeQ7I4S+AqFwqExpn02\npmB2ZpTAVygUDs0Ag8D/Q5VMVAJfoVA4NkE+7kwbEMZX28+wNzmfGr0kt6SSgjLnK5+ojLYKhcLh\neerCwaw/uoH5b202tXX392TrYzOcypCrVvgKhcLhiQn1qdeWUVjOzsQ8K70dFyXwFQqFwyOE4Pap\nfYgK9mbTo9NZ//A0PN10/LrPucokKoGvUCicgsfOH8iGR6bRK9ib6FAfpsaGseJgBjX65mUbyCup\n5HR2CZ9vS6IzZShoCUqHr1AonIK6uvp5wyNYeegs+1MLGNkrEIDKaj3urto6uLyqhooqPQHebuSW\nVDL6uVWma0dGBjIssu3VvjoatcJXKBT/397dx1ZV33Ecf39KW1YKllIIjyIFeRi68TgGA9wcLg4Y\nMmIWTaY40bFNQ9yWzEBgTh3ZBtE9xWh48InhNIy5DassDjTDKEMeREBAaSkCFUYZ8igPLXz3x/m1\n3JanXtrS9tzvK7m55/7OPfecz2377bnnnPv7paQeYdD0NTsOULjvKD9auJZeM5by2sY9FO8/xt3P\nrmbE7DfYf/QkT75ZWGXZDSUH62w7So+cZPDMZazbWf/nE3wP3zmXktq1ikbQmvnqFma+uqWy/b4X\n1lV53qylW/nL2t1V2ko+PZ7UusyMwyfKycnKOGfesF8vp/yMMeffRcy585L9n9WK7+E751JSm+zM\nKo9H9mx73udVFPt+XXIY+4WOpKeJkoM1L/hHTpSRP+01+j3yOqu2Vx2YZcVHpZSHcwgtMut//9v3\n8J1zKSkjYaDz7b8aQ1qa+PzP/8nxstM8/p1+3DqoC6+8/wkLVu5g9PUdmTCgM7nZmdw2ZyVb9xzh\n9Bljy57DFJUeZXz/zhdcz7vFZ4cCmfTcalY8eCN5LZtz5owx8ZloHN6v9mrHsB559Za1ghd851zK\nmjdxMHsPnyAtLTqhO/mG7vxh+TaGXxvt7Y/r14lx/TpVWaZzbharig/Qe8bSyr3z3h1a0afDVQAc\nOHaKYyfLOXS8jN4dWrGy6H9kpqfRu30rNpYc4pYn3mbhvV/mtjkrAbj/xh787OY+VySvD4DinHOB\nmfHpZ2XnHO5J9Hbhfr47f1WVtpE927Jg0hDW7zrIhCffqWz//sh8Fq/dzcCuuTw0ri93P7ea7aXH\nKucP6daGOXcOIvci66uJKzIAiqSHJZWE4Q3XSxqTMG+apEJJH0q6uTbrcc65K0HSRYs9wPBr21Iw\nZQQQnfht2zKTt7bt5/l3dlQp9gDz3irm8IlypozqyTV52fztvuGEDxPkZWey6IfDal3sk1EXh3R+\nZ2aPJTZI6gvcDlwHdAKWSeplZj6qsHOuybu+cw47fjMWgEPHy/jSzGU8/MrZUbW6t8smJyuD93Ye\nZNatX6y8zj8nK4Ne7Vuxde8R7hmZf8W3u76O4Y8HXjKzk0CxpEJgCLCyntbnnHMNIicrg6mj+/Bo\nwWbS00RhGF6x/PQZPj7wGd2r9ePzi3HX8WjBZoZ1r/+TtNXVxWWZUyRtkPSMpNzQ1hnYlfCc3aHN\nOediZ3z/TrRukcFD4/pWtqU3S6NHu5bnfMN3WI88lj4wkgFdc6u/TL275B6+pGVAh/PMmg48BfwS\nsHD/ODApmQ2QNBmYDNC1a9dkFnXOuUYhr2Vz1s34RuXVPo3VJQu+md1UkxeSNA8oCA9LgKsTZncJ\nbed7/bnAXIiu0qnJupxzrrFp7MUean+VTseEhxOATWF6CXC7pOaS8oGewLu1WZdzzrnaqe1J29mS\n+hMd0tkB/ADAzD6QtAjYDJQD9/sVOs4517Aa1RevJJUCH9fiJdoC++toc5qCVMsLnjlVeObkXGNm\n7S71pEZV8GtL0pqafNssLlItL3jmVOGZ64f3lumccynCC75zzqWIuBX8uQ29AVdYquUFz5wqPHM9\niNUxfOeccxcWtz1855xzFxCLgi/pm6Eb5kJJUxt6e+qKpKslvSlps6QPJD0Q2ttI+pekbeE+N2GZ\nJt8ttaRmkt6TVBAexzovgKTWkhZL2ippi6Rhcc4t6Sfhd3qTpBclfS6OeUMfY/skbUpoSzqnpEGS\nNoZ5f1T1Dnpqysya9A1oBhQB3YFM4H2gb0NvVx1l6wgMDNOtgI+AvsBsYGponwrMCtN9Q/7mQH54\nX5o1dI7LyP1T4M9AQXgc67why/PAvWE6E2gd19xEHSkWA1nh8SLge3HMC9wADAQ2JbQlnZOop4Kh\ngIClwOjL2Z447OEPAQrNbLuZnQJeIuqeuckzsz1mti5MHwG2EP2xjCcqEIT7b4fpym6pzawYqOiW\nusmQ1AUYC8xPaI5tXgBJOUSF4WkAMztlZgeJd+50IEtSOtAC+IQY5jWzFcCBas1J5Qxd2FxlZv+x\nqPovSFgmKXEo+CnRFbOkbsAAYBXQ3sz2hFl7gfZhOg7vxe+BB4EzCW1xzgvR3lwp8Gw4lDVfUjYx\nzW1mJcBjwE5gD3DIzF4npnnPI9mcncN09fakxaHgx56klsBfgR+b2eHEeeE/fiwutZL0LWCfma29\n0HPilDdBOtHH/qfMbABwjOijfqU45Q7HrMcT/aPrBGRLuiPxOXHKezFXOmccCn6Nu2JuiiRlEBX7\nF8zs5dD834qeSsP9vtDe1N+L4cAtknYQHZr7uqSFxDdvhd3AbjOrGBl7MdE/gLjmvgkoNrNSMysD\nXga+QnzzVpdszpIwXb09aXEo+KuBnpLyJWUSjaW7pIG3qU6EM/FPA1vM7LcJs5YAd4Xpu4B/JLQ3\n2W6pzWyamXUxs25EP8c3zOwOYpq3gpntBXZJ6h2aRhH1NBvX3DuBoZJahN/xUUTnp+Kat7qkcobD\nP4clDQ3v18SEZZLT0Gex6+hM+BiiK1iKgOkNvT11mGsE0ce9DcD6cBsD5AHLgW3AMqBNwjLTw/vw\nIZd5Jr8x3ICvcfYqnVTI2x9YE37Wfwdy45wbeATYSjSGxp+IrkyJXV7gRaLzFGVEn+TuuZycwODw\nXhUBTxC+NJvszb9p65xzKSIOh3Scc87VgBd855xLEV7wnXMuRXjBd865FOEF3znnUoQXfOecSxFe\n8J1zLkV4wXfOuRTxfzDyIbFKUfToAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fdaa048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(2,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11176b438>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1[0:10].plot(ax=ax[0], label='S1', kind='bar')\n",
    "s2.plot(ax=ax[1], label='S2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hXN69KWampCASRFGREURFRjCgXRIAv5q0iLYNa7N4y37GXtKJoZ20JK34lPdc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\np387HlgDdAaeAkb7y0cD/+f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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1116556a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
